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检索条件"任意字段=Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2014"

共 283 条记录，以下是101-110 订阅

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Application of the JDL Data fusion Process Model for Cyber Security

Application of the JDL Data Fusion Process Model for Cyber S...

引用

Conference on multisensor, multisource information fusion - architectures, algorithms and applications 2010

作者： Giacobe, Nicklaus A. Penn State Univ Coll Informat Sci & Technol University Pk PA 16802 USA

ISBN: (纸本)9780819481740

A number of cyber security technologies have proposed the use of data fusion to enhance the defensive capabilities of the network and aid in the development of situational awareness for the security analyst. While there have been advances in fusion technologies and the application of fusion in intrusion detection systems (IDSs), in particular, additional progress can be made by gaining a better understanding of a variety of data fusion processes and applying them to the cyber security application domain. This research explores the underlying processes identified in the Joint Directors of Laboratories (JDL) data fusion process model and further describes them in a cyber security context.

关键词： Cyber Security Network Security Data fusion JDL Data fusion Process Model Situational Awareness

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Classification of terrain using multi-resolution satellite/aerial imagery and LiDAR data

Classification of terrain using multi-resolution satellite/a...

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Conference on multisensor, multisource information fusion - architectures, algorithms and applications 2010

作者： Kocher, Brian R. Thomas, Alan M. Georgia Inst Technol Georgia Tech Res Inst Atlanta GA 30332 USA

ISBN: (纸本)9780819481740

High resolution LiDAR data is used to augment spectral data to improve resolution/accuracy. Digital elevation information, texture information, and spectral data are all combined into a single dataset and different clustering algorithms are used on the raster information and compared with clusters of spectral data alone. Long term goals of the work are to find efficient and effective methods of combining different data sets of varying resolution from different sources into a single dataset for analysis to improve data and classification resolution and accuracy.

关键词： image fusion image processing texture multispectral imagery lidar data material classification

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Dynamic image fusion and general observer preference

Dynamic image fusion and general observer preference

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Conference on multisensor, multisource information fusion - architectures, algorithms and applications 2010

作者： Burks, Stephen D. Doe, Joshua M. USA RDECOM CERDEC Night Vis & Elect Sensors Directorate Ft Belvoir VA 22060 USA

ISBN: (纸本)9780819481740

Recent developments in image fusion give the user community many options for ways of presenting the imagery to an end-user. Individuals at the US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate have developed an electronic system that allows users to quickly and efficiently determine optimal image fusion algorithms and color parameters based upon collected imagery and videos from environments that are typical to observers in a military environment. After performing multiple multi-band data collections in a variety of military-like scenarios, different waveband, fusion algorithm, image post-processing, and color choices are presented to observers as an output of the fusion system. The observer preferences can give guidelines as to how specific scenarios should affect the presentation of fused imagery.

关键词： Image fusion Sensors Cameras Image processing Video Image sensors Data fusion Algorithm development Medium wave Environmental sensing

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Technical Overview of the Sarnoff Acadia II Vision Processor

Technical Overview of the Sarnoff Acadia II Vision Processor

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Conference on multisensor, multisource information fusion - architectures, algorithms and applications 2010

作者： van der Wal, Gooitzen S. Sarnoff Corp Princeton NJ 08540 USA

ISBN: (纸本)9780819481740

The Sarnoff Acadia (R) II is a powerful vision processing SoC (System-on-a-Chip) that was specifically developed to support advanced vision applications where system size, weight and/or power are severely constrained. This paper, targeted at vision system developers, presents a detailed technical overview of the Acadia (R) II, highlighting its architecture, processing capabilities, memory and peripheral interfaces. All major subsystems will be covered, including: video preprocessing, specialized vision processing cores for multi-spectral image fusion, multi-resolution contrast normalization, noise coring, image warping, and motion estimation. Application processing via the MPCore (R), an integrated set of four ARM (R) 11 floating point processors with associated peripheral interfaces is presented in detail. The paper will emphasize the programmability of the Acadia (R) II, while describing its ability to provide state-of-the-art real-time image processing in a small, power optimized package.*

关键词： Real-time Multiresolution Vision processing Image fusion Stabilization Embedded Processing Multicore multi-spectral

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Multi-Layered Context Impact Modulation for Enhanced Focus of Attention of Situational Awareness in Persistent Surveillance Systems

Multi-Layered Context Impact Modulation for Enhanced Focus o...

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Conference on multisensor, multisource information fusion - architectures, algorithms and applications 2010

作者： Shirkhodaie, Amir Rababaah, Haroun Tennessee State Univ Dept Mech & Mfg Engn Ctr Excellence Battlefield Sensor Fus Nashville TN 37209 USA

ISBN: (纸本)9780819481740

This paper presents a Multi-Layered Context Impact Modulation (MCIM) technique for persistent surveillance systems (PSS) and discusses its layered architecture for different context modulations including: spatial, temporal, sensor reliability, human presence, and environmental modulations. This paper also presents a fusion model for enhancement of focus of attention at the common operation picture (COP). The fusion model combines all the impacts from the different MCIM layers onto one unified modulated map. To test and evaluate the performance of MCIM, several experiments were conducted to modulate interaction of humans and vehicles which exhibit various normal and suspicious behaviors. The experimental results show strength of this approach in correctly modulating different suspicious situations with higher degree of certainty.

关键词： Persistent Surveillance Systems Situation Assessment Context Impact Layered Modulation Energy Logic fusion Engine Large-scale Sensor Networks Soft fusion

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Implementing Real-Time Imaging Systems Using the Sarnoff Acadia II Vision Processor

Implementing Real-Time Imaging Systems Using the Sarnoff Aca...

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Conference on multisensor, multisource information fusion - architectures, algorithms and applications 2010

作者： Berends, David van der Wal, Gooitzen Sarnoff Corp Princeton NJ 08543 USA

ISBN: (纸本)9780819481740

Vision system designers often face the daunting challenge of implementing powerful image processing capabilities in severely size, weight and power constrained systems. Multi-sensor fusion, image stabilization, image enhancement, target detection and object tracking are fundamental processing techniques required by UAVs (Unmanned Aerial Vehicles), smart cameras, weapon sights, and vehicle situational awareness systems. All of these systems also process non-vision data while communicating large amounts of information elsewhere. To meet their demanding requirements, Sarnoff developed the Acadia (R) II System-on-a- Chip, combining dedicated image processing cores, four ARM (R) 11 processors and an abundance of peripherals in a single Integrated Circuit. This paper will describe how to best use the power of the Acadia (R) II as both an all-in-one image processor and as a general purpose computer for performing other critical non-vision tasks, such as flight control and system-to-system communication.*

关键词： fusion stabilization image enhancement size weight and power constrained systems target detection object tracking system-on-a-chip situational awareness

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Global evaluation of focussed Bayesian fusion

Global evaluation of focussed Bayesian fusion

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Conference on multisensor, multisource information fusion - architectures, algorithms and applications 2010

作者： Sander, Jennifer Heizmann, Michael Goussev, Igor Beyerer, Juergen Karlsruhe Inst Technol KIT Inst Anthropomat IFA Vis & Fus Lab Adenauerring 4 D-76131 Karlsruhe Germany Fraunhofer Inst Optron Syst Technol & Image Explo D-76131 Karlsruhe Germany

ISBN: (纸本)9780819481740

information fusion is essential for the retrieval of desired information in a sufficiently precise, complete, and robust manner. The Bayesian approach provides a powerful and mathematically funded framework for information fusion. By local Bayesian fusion approaches, the computational complexity of Bayesian fusion gets drastically reduced. This is done by a concentration of the actual fusion task on its probably most task relevant aspects. In this contribution, further research results on a special local Bayesian fusion technique called focussed Bayesian fusion are reported. At focussed Bayesian fusion, the actual Bayesian fusion task gets completely restricted to the probably most relevant parts of the range of values of the Properties of Interest. The practical usefulness of focussed Bayesian fusion is shown by the use of an example from the field of reconnaissance. Within this example, final decisions are based on local significance considerations and consistency arguments. As shown in previous publications, the absolute values of focussed probability statements represent upper bounds for their global values. Now, lower bounds which are obtained from the knowledge about the construction of the focussed Bayesian model are proven additionally. The usefulness of the resulting probability interval scheme is discussed.

关键词： information fusion Bayesian fusion local Bayesian fusion focussed Bayesian fusion Maximum Entropy principle probability interval scheme probability bounds restricted model qualitative analysis quantitative analysis

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An Orientation-based fusion Algorithm for multisensor Image fusion

An Orientation-based Fusion Algorithm for Multisensor Image ...

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Conference on multisensor, multisource information fusion - architectures, algorithms and applications 2010

作者： Zheng, Yufeng Alcorn State Univ Alcorn State MS 39096 USA

ISBN: (纸本)9780819481740

Multiscale fusion algorithms (wavelet or pyramid) can generally satisfy multisensory image fusion. However, those algorithms are not ideal to fuse visible images and infrared images whose intensities appear inverted. Therefore, a novel orientation-based fusion algorithm is proposed in this paper to address this problem. Specifically, a set of MxN Gabor wavelet transforms (GWT) are performed with two input images (I-A and I-B). At each frequency band (b = 1, 2, ..., M), the index of maximal GWT magnitude between two images is selected pixel by pixel;and then two index frequencies, H-A(b) and H-B(b), are calculated as its index accumulation along N orientations, respectively. The final HA and HB are the weighted summations through M bands, where the band weights (W-b) are given empirically. Eventually, the fused image is computed as I-F = (I-A.* H-A + I-B.* H-B)/(H-A + H-B), where '.*' denotes element-by-element product of two arrays. The orientation-based fusion algorithm can be further varied by either keeping DC (direct current) or suppressing DC in GWT. "Keeping DC" will produce a contrast-smooth image;while "suppressing DC" will result a sharpened fusion. Color fusion is achieved by replacing the red channel of a color image with the fused image, which is suitable for poorly illuminated color images. Not only are the fused images of visible and infrared images satisfied, but the fusions of other image sets are also comparable to the results of multiscale fusion algorithms. The proposed algorithm can be applied to multiple (more than two) image fusion.

关键词： Gabor wavelet transforms (GWT) multiscale image fusion multisensory image fusion

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Long-duration Fused Feature Learning Aided Tracking

Long-duration Fused Feature Learning Aided Tracking

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Conference on multisensor, multisource information fusion - architectures, algorithms and applications 2010

作者： Ivey, Richard Horn, Joel Merkert, Raimund Boston Univ Dept Cognit & Neural Syst 677 Beacon St Boston MA 02215 USA

ISBN: (纸本)9780819481740

Multiple-hypothesis tracking (MHT) algorithms solve the report-to-track association problem(1-5) by accumulating kinematic evidence provided by one or more sensors over time to find likely correlations in the data. MHT technologies have long been applied to such problems as machine vision;automatic target tracking using radar moving target indicator (MTI) for ground, air, sea, and space vehicles;and video-based object tracking. However, relying on kinematic information alone to maintain reliable track in a multi-target scenario is problematic due to a plethora of issues such as sensor limitations, obscuration of the targets, or target/confuser proximity.(6-7) We present our track fusion algorithm, the Long-term Hypothesis Tree (LTHT) that solves the tracklet-to-tracklet association problem by using signature information to repair errors in kinematic tracks. LTHT provides a framework for using arbitrary target signatures such as spectral or shape characteristics to correct errors made by an MHT tracker. The LTHT represents high-level interactions among complex tracks by condensing kinematic track trajectories into a compact representation that can be efficiently maintained over much longer temporal scales than typical MHT trees.

关键词： information fusion multiple-hypothesis tracking radar tracking machine vision

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Fast Color-Transfer-Based Image fusion Method for Merging Infrared and Visible Images

Fast Color-Transfer-Based Image Fusion Method for Merging In...

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Conference on multisensor, multisource information fusion - architectures, algorithms and applications 2010

作者： Li, Guangxin Xu, Shuyan Zhao, Xin Chinese Acad Sci Changchun Inst Opt Fine Mech & Phys Changchun 130033 Peoples R China Changchun Univ Changchun 130022 Peoples R China

ISBN: (纸本)9780819481740

We present a computationally efficient color image fusion algorithm for merging infrared and visible images. At the core of the proposed method is the color transfer technique based on the linear YCBCR space. The method directly uses the grayscale fused image and the difference signals of the input images to construct the source YCBCR components, then uses the statistical color transfer technique to form a color fused image that takes the target image's color characteristics. Two different strategies, which respectively employ the pixel averaging fusion scheme and the multiresolution fusion scheme as the grayscale image fusion solution, are proposed to fulfill different user needs. The simple strategy using the pixel averaging fusion scheme answers to a need of easy implementation and speed of use. And the complex strategy using the multiresolution fusion scheme answers to the high quality need of the fused products. In addition, we also describe some useful theories about color-transfer-based image fusion. Experimental results show that the proposed color image fusion algorithm can effectively produce a natural appearing "daytime-like" color fused image, and even using the pixel averaging fusion scheme to implement the grayscale fusion can also provide a pleasing result.

关键词： color image fusion color transfer YCBCR transformation infrared image visible image night vision

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